Scientists from DOE’s Pacific Northwest National Laboratory, DOE’s Sandia National Laboratories, and the Georgia Institute of Technology will collaborate on solutions to some of the most challenging problems in AI today, thanks to $5.5 million in funding from DOE.
While high-energy physics and cosmology seem worlds apart in terms of sheer scale, physicists and cosmologists at Argonne are using similar machine learning methods to address classification problems for both subatomic particles and galaxies.
What did Vincent van Gogh actually paint and draw? Paintings and drawings fade, so researchers from TU Delft are using deep learning to digitally reconstruct works of art and discover what they really looked like. ‘What we see today is not the painting or drawing as it originally was,’ says researcher Jan van der Lubbe.
The complexity of cities and the interrelationships of urban systems makes them ideal candidates for research using machine learning, which Argonne scientists are deploying to improve cities.
Experts in the use of artificial intelligence (AI) in radiology, from many of the world’s leading radiology, medical physics and imaging informatics groups, today published an aspirational statement to guide the development of AI in radiology.
Argonne to become newest member of Accelerating Therapeutics for Opportunities in Medicine (ATOM) consortium.
Eighth annual SINAInnovations festival on October 15-16 at Icahn School of Medicine at Mount Sinai in New York City
The U.S. Department of Energy (DOE) will convene a meeting Oct. 2-3, with top experts from across government, academia and industry to discuss future efforts in Artificial Intelligence (AI).
From 20 minutes or more to 10 seconds. Researchers from Intermountain Healthcare and Stanford University say 10 seconds is about how quickly a new system they studied that utilizes artificial intelligence took to accurately identify key findings in chest X-rays of patients in the emergency department suspected of having pneumonia.
University of Texas at Dallas researchers have demonstrated that imaging technology used to map the universe shows promise for more accurately and quickly identifying cancer cells in the operating room.
Scientists have developed a computer method that may help improve understanding and treatment of Crohn’s disease, which causes inflammation of the digestive tract. The Rutgers-led study, published in the journal Genome Medicine, used artificial intelligence to examine genetic signatures of Crohn’s in 111 people. The method revealed previously undiscovered genes linked to the disease, and accurately predicted whether thousands of other people had the disease.
A team of college interns at Sandia National Laboratories has built autonomous drones to try out new navigation, guidance and control, and target recognition techniques ultimately bound for autonomous hypersonic vehicles.
For the first time, a sophisticated computer model has been shown to accurately predict two of the most challenging side effects associated with radiation therapy for head and neck cancer. This precision oncology approach has the potential to better identify patients who might benefit from early interventions that may help to prevent significant weight loss after treatment or reduce the need for feeding tube placement. Findings were presented at the 61st Annual Meeting of the American Society for Radiation Oncology (ASTRO).
A trigger system powered by predictive analytics increased palliative care consultations by 74 percent after implementation
Two studies led by UT Southwestern provide evidence for the impact of biology by using artificial intelligence to identify patterns of brain activity that make people less responsive to certain antidepressants. Put simply, scientists showed they can use imaging of a patient’s brain to decide whether a medication is likely to be effective.
FAU's Master of Science in Artificial Intelligence is an innovative degree program and training curriculum that will educate students and train professionals to develop new skills for jobs that are not yet defined and be part of the first generation of an AI-and-autonomy workforce.
To accelerate promising artificial intelligence applications in diverse research fields, ORNL has established a labwide AI Initiative. This internal investment brings the lab’s AI expertise, computing resources and user facilities together to facilitate analyses of massive datasets.
The American College of Radiology (ACR) and the Society for Imaging Informatics in Medicine (SIIM) announced the official results of their first machine learning challenge today during the SIIM-ACR Pneumothorax Challenge ceremony at SIIM’s 4th annual Conference on Machine Intelligence in Medical Imaging (C-MIMI).
A new artificial intelligence (AI) tool available for free in a smartphone app can predict near-term crop productivity for farmers in Africa and may help them protect their staple crops
Technical sessions at this year’s conference centered around four thematic areas: Autonomous Systems, Nanophotonics and Plasmonics, Virtual Reality and Augmented Vision, as well as Quantum Technologies.
Researchers at Michigan State University say that true, human-level intelligence remains a long way off, but their new paper published in The American Naturalist explores how computers could begin to evolve learning in the same way as natural organisms did – with implications for many fields, including artificial intelligence.
Combining new classes of nanomembrane electrodes with flexible electronics and a deep learning algorithm could help disabled people wirelessly control an electric wheelchair, interact with a computer or operate a small robotic vehicle without donning a bulky hair-electrode cap or contending with wires.
A team of scientists has developed a computational model that uses artificial intelligence to find sites for hydropower dams in order to help reduce greenhouse gas emissions.
Understanding the how our universe came to be what it is today and what will be its final destiny is one of the biggest challenges in science.
Irvine, Calif., Sept. 17, 2019 – An interdisciplinary team of scientists at the University of California, Irvine has developed a new technique for predicting the final size of a wildfire from the moment of ignition. Built around a machine learning algorithm, the model can help in forecasting whether a blaze is going to be small, medium or large by the time it has run its course – knowledge useful to those in charge of allocating scarce firefighting resources.
A team of researchers, including faculty at Binghamton University, have developed machine learning algorithms which can successfully identify bullies and aggressors on Twitter with 90 percent accuracy.
The ability to learn and adapt in real time is a central feature of biological systems. Researchers at the U.S. Department of Energy’s (DOE) Argonne National Laboratory are exploring the use of neuromorphic computer chips that demonstrate this versatility to enhance our ability to efficiently process information in space and in other extreme environments.
Ecker became chair of Brookhaven’s Nuclear Science and Technology Department in October 2018, bringing expertise in nuclear reactor materials.
Machine learning could lead to automated processes that would allow soybean producers to diagnose crop stresses more efficiently. A multi-disciplinary team at Iowa State University recently received a grant to develop the technology, which could lead to unmanned aerial vehicles surveying fields and automatically analyzing crop images.
A new synthetic material that creates a linked sensory network similar to a biological nervous system could enable soft robots to sense how they interact with their environment and adjust their actions accordingly.
Iowa State researchers are using machine-learning tools to clean up thunderstorm reports compiled by the National Weather Service. The goal is to determine which reports accurately describe storms that had severe winds. Accurate data could lead to new tools that predict severe thunderstorm winds.
The prediction of molecular reactions triggered by light is to date extremely time-consuming and therefore costly. A team led by Philipp Marquetand from the Faculty of Chemistry at the University of Vienna has now presented a method using artificial neural networks that drastically accelerates the simulation of light-induced processes.
Mayo Clinic and Google announced a 10-year strategic partnership on Tuesday, Sept. 10. This partnership will redefine how health care is delivered and accelerate the pace of health care innovation through digital technologies.
Ablacon, Inc. (www.ablacon.com), an Ajax Health-funded company, announced today the release of an updated version of its Ablamap technology under the company's existing CE Mark.
The Department of Energy has announced Argonne National Laboratory will be receiving funding for two new projects in data science to accelerate discovery in chemistry and material sciences.
It is increasingly common to use robots in war zones to examine and disarm hazards or recover objects with the understanding that the loss of a robot is a far more acceptable outcome than the death of a solider.
• In two different studies, researchers used machine learning algorithms to classify kidney biopsy samples and found substantial agreement with standard classification by pathologists • The methods may augment traditional diagnostics of kidney disease.
St. Jude Children’s Research Hospital scientists have taken whole genome sequencing to the next level by creating a 3D map of the genome to better understand development and disease
A collaboration between scientists at the Danforth Center and Washington University in St. Louis have developed a four-year research project that garnered $3 million in support from the National Science Foundation to study how plants react to increased levels of CO2 over generations.
Researchers in Lawrence Berkeley National Laboratory's Center for Advanced Mathematics for Energy Research Applications have been working with beamline scientists at Brookhaven National Laboratory to develop and test SMART, a mathematical method that enables autonomous experimental decision making without human interaction.
Researchers have developed a machine learning approach called transfer learning that lets them model novel materials by learning from data collected about millions of other compounds. The new approach can be applied to new molecules in milliseconds, enabling research into a far greater number of compounds over much longer timescales.
Nine-month-old brains-in-a-dish and the brains of premature newborn babies generate similar electrical patterns, as captured by electroencephalogram (EEG) — the first time such brain activity has been achieved in a cell-based laboratory model.
Before self-driving vehicles become a permanent fixture on our roads they need to overcome two challenges—figuring out where they are and their range of motion (localization) and modeling their surroundings to avoid running into stuff (mapping). In the world of robotics, it’s called SLAM—simultaneous localization and mapping. Researchers at the University of Delaware have developed novel SLAM algorithms that offer the best solution to date for giving these vehicles a sense of direction.
A study conducted by researchers from the Cancer Science Institute of Singapore (CSI Singapore) at the National University of Singapore and the School of Biological Sciences at Nanyang Technological University, Singapore (NTU Singapore) revealed a common deficiency in existing artificial intelligence methods used to predict enhancer–promoter interactions, that may result in inflated performance measurements.
The U.S. Department of Energy (DOE) announced $21.4 million in funding for research in Quantum Information Science (QIS) related to both particle physics and fusion energy sciences.
Humans and machines worked together to help train an artificial intelligence -- AI -- model that outperformed other clickbait detectors, according to researchers. In addition, the new AI-based solution was also able to tell the difference between clickbait headlines that were generated by machines -- or bots -- and ones written by people.
UPTON, NY - A team of scientists from the U.S. Department of Energy's Brookhaven National Laboratory and Lawrence Berkeley National Laboratory designed, created, and successfully tested a new algorithm to make smarter scientific measurement decisions.
The University of Adelaide will lead a new national mining research and training centre utilising advanced technologies that will help to shape the future of Australia’s mining operations.
RSS
Medicine keyboard_arrow_right
Sciencekeyboard_arrow_right
Life keyboard_arrow_right
Business keyboard_arrow_right
Journal News keyboard_arrow_right
By Location keyboard_arrow_right
Meetings, Grants, and Events keyboard_arrow_right